Lowly Jellyfish Uses High-Tech Strategy to Find Food

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The barrel jellyfish, isn't just the largest jelly found in the
waters around the United Kingdom, it's also one of the animal
kingdom's most strategic searchers, according to a new study.

To locate the best possible meal in the vast waters of its marine
habitat, the barrel jellyfish (Rhizostoma octopus) uses
a strategy most commonly associated with the
world's fastest supercomputers — an approach known as fast
simulated annealing.

For mathematicians, fast simulated annealing is an algorithm,
implemented by a supercomputer, which can find optimal solutions
to complex problems in a relatively short amount of time. For
jellyfish, fast simulated annealing is a highly evolved
search strategy categorized by a series of predictable movements
that bring the jelly closer and closer to large numbers of
plankton, its preferred prey. [ Album:
Amazing Photos of Jellyfish Swarms ]

This complex search strategy has never been observed before in
nature, according to study lead author Andy Reynolds, a scientist
at Rothamsted Research, an agricultural research center in the
U.K.

Yet, other
mathematical patterns of movement have been widely observed
in the natural world, Reynolds said. The most common of these
patterns, the "Lévy walk," is a less complex version of the
barrel jelly's approach.

"A Lévy walk is [a] random walk in which frequently occurring
small steps are interspersed with more rarely occurring longer
steps, which in turn are interspersed with even rarer, even
longer steps and so on," Reynolds told Live Science in an email.
(The Lévy walk was named after French mathematician Paul Lévy,
who was noted for his work in the theory of probability.)

While this may sound like a fairly complex way of searching for
something, Reynolds said it's similar to the way you might search
for your lost car keys in the living room sofa and then, not
finding them there, head over to the closet to check your coat
pocket.

"This hierarchical nested pattern is highly effective when
searching because once an area has been intensively surveyed, the
searcher is relocated to another area and then begins a new bout
of intensive searching," Reynolds said. [ Marine
Marvels: Spectacular Photos of Sea Creatures ]

Some of the species that have been observed using Lévy walks to
locate their meals include sharks, penguins, honeybees, ants,
turtles and even
human hunter-gatherers.

But among these many species, the barrel jelly stands out
because, in addition to exhibiting this Lévy walk pattern, it
also engages several search methods that others species don't
seem to use.

Move like a jellyfish

One of the barrel jelly's search-optimizing behaviors, often
referred to as a "bounce," occurs when the jellyfish starts out
in one depth of water and then makes a long glide either upwards
or downwards to a different depth of water. If it doesn't find a
meal in the new location, the jellyfish will "bounce" again to
return to its original position.

Some scientists believe that the jelly's tendency to bounce
around in the water may actually hinder its ability to search for
food, but according to Reynolds, these unusual animals have had
it right all along.

The jellyfish, which will sometimes repeat its pattern of bounces
dozens of times a day, uses this strategy to slowly home in on
the highest concentrations of plankton, Reynolds explained.

The behavior therefore makes the barrel jelly even more efficient
than other marine animals, such as penguins and sharks, that only
use Lévy walks to search for prey, Reynolds said.

The answer has to do with diet, Reynolds said. The barrel
jellyfish benefits from spending long periods of time
searching for concentrations of prey because it needs to eat
a lot of plankton before it is satisfied, Reynolds said. This is
different from sharks and penguins, which Reynolds said can
survive by eating the occasional fish.

"A Lévy search is highly effective in finding the next meal, when
any meal will do. Fast simulated annealing, on the other hand,
takes the forager to the best possible meal," Reynolds said.
"This is what makes jellyfish special — they are very discerning
diners, unlike bony fish, penguins, turtles and sharks, which are
just looking for any meal."

This high level of discernment is also what draws certain
mathematicians and engineers to the strategy of fast simulated
annealing for
supercomputing, Reynolds said.

Based on mathematical and computer models, Reynolds' study found
that like barrel jellyfish, mathematicians tend to implement this
strategy only when they're looking for the best possible solution
to a problem, not a variety of potential solutions.

The new study was published online today (Aug. 5) in the Journal
of the Royal Society Interface.